Following [1]}, we validate our framework on three benchmark datasets in few-shot learning.
1) CIFAR100 [2]} consists of \(60,000\)  images, evenly distributed in 100 classes (64 classes for training, 10 classes for validation, and 25 classes for testing). 2) miniImageNet [3]} is a subset of ImageNet, with \(60,000\)  images from 100 classes (64 classes for training, 16 classes for validation, and 20 classes for testing). 3) FEMNIST [4]} is a dataset with \(805, 263\)  handwritten characters in 62 classes (42 classes for training, 10 classes for validation, and 10 classes for testing).
